Laneform utilizes generative AI technology to aid urban planners, developers, and civic leaders in creating conceptual imagery. The platform enables effective community engagement by allowing users to participate in visual surveys. It enhances the planning process by providing realistic renderings and gathering public feedback efficiently.

The Multi-Agent Autonomous Waste Collection System is a research-driven platform that employs multi-agent reinforcement learning to train individual waste-collecting robots to collaborate on route planning. Agents learn to avoid redundant coverage, minimize travel distance, and respond to dynamic waste generation patterns. Built in Python, the system integrates a simulation environment for testing and refining policies before real-world deployment. Users can configure map layouts, waste drop-off points, agent sensors, and reward structures to tailor behavior to specific urban areas or operational constraints.